Correlation Between Bank of America and Multi-index 2030
Can any of the company-specific risk be diversified away by investing in both Bank of America and Multi-index 2030 at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Bank of America and Multi-index 2030 into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of America and Multi Index 2030 Lifetime, you can compare the effects of market volatilities on Bank of America and Multi-index 2030 and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Bank of America with a short position of Multi-index 2030. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Multi-index 2030.
Diversification Opportunities for Bank of America and Multi-index 2030
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Multi-index is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Multi Index 2030 Lifetime in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Multi Index 2030 and Bank of America is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Bank of America are associated (or correlated) with Multi-index 2030. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Multi Index 2030 has no effect on the direction of Bank of America i.e., Bank of America and Multi-index 2030 go up and down completely randomly.
Pair Corralation between Bank of America and Multi-index 2030
Considering the 90-day investment horizon Bank of America is expected to generate 2.93 times more return on investment than Multi-index 2030. However, Bank of America is 2.93 times more volatile than Multi Index 2030 Lifetime. It trades about 0.08 of its potential returns per unit of risk. Multi Index 2030 Lifetime is currently generating about 0.2 per unit of risk. If you would invest 4,443 in Bank of America on May 20, 2025 and sell it today you would earn a total of 251.00 from holding Bank of America or generate 5.65% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.41% |
Values | Daily Returns |
Bank of America vs. Multi Index 2030 Lifetime
Performance |
Timeline |
Bank of America |
Multi Index 2030 |
Bank of America and Multi-index 2030 Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and Multi-index 2030
The main advantage of trading using opposite Bank of America and Multi-index 2030 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Multi-index 2030 can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Multi-index 2030 will offset losses from the drop in Multi-index 2030's long position.Bank of America vs. JPMorgan Chase Co | Bank of America vs. Citigroup | Bank of America vs. Wells Fargo | Bank of America vs. Toronto Dominion Bank |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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